Nutrition preparation optimization method for breeding procambarus clarkii

Abstract

The invention relates to the field of aquaculture nutrition preparation optimization, and particularly discloses a nutrition preparation optimization method for procambarus clarkii culture, which comprises the following steps of: setting a feeding time point, introducing temperature prediction data of the day before feeding, and according to the relationship between the feeding activeness of procambarus clarkii and the temperature # imgabs0 #, determining the feeding activeness of procambarus clarkii according to the relationship between the feeding activeness of procambarus clarkii and the temperature # imgabs0 #; and calculating to obtain a post-feeding weighted ingestion coefficient and a post-feeding ingestion stability coefficient, so that nutrition preparation can dynamically respond to temperature change, and the actual ingestion capability of the crayfish can be better met. According to the method, an adjustment factor model is established based on the growth stage of the crayfish and the calculated after-feeding weighted ingestion coefficient and after-feeding ingestion stability coefficient, the proportion of all nutritional ingredients is optimized, and the influence of the average ingestion capacity and ingestion stability is fully considered.

Description

Technical Field

[0001] The invention belongs to the technical field of aquaculture nutrient preparation optimization, and in particular relates to a nutrient preparation optimization method for Procambarus clarkii culture. Background Art

[0002] Procambarus clarkii (commonly known as crayfish) has become an important species in the aquaculture industry due to its delicious taste, rich nutrition and high market demand. In order to improve the breeding efficiency of Procambarus clarkii, the optimization of the nutritional formula of feed is crucial. Traditional crayfish feed formula is usually based on experience or simple nutritional demand analysis, and fails to fully consider the important effects of temperature and growth stage. This approach may lead to unbalanced feed nutrition and low feeding efficiency, which is not conducive to the breeding of Procambarus clarkii. Summary of the invention

[0003] In order to overcome the technical problems described in the above background technology, the present invention provides a method for optimizing the nutritional preparation for the cultivation of Procambarus clarkii, by setting the feeding time point, introducing the temperature forecast data of the day before feeding, and optimizing the nutritional preparation according to the feeding activity of Procambarus clarkii and the temperature. The relationship between the weighted feeding coefficient and the feeding stability coefficient after feeding is calculated, which enables the nutritional formulation to dynamically respond to temperature changes and better meet the actual feeding capacity of crayfish.

[0004] The technical solution of the present invention is: a method for optimizing the nutritional preparation for the cultivation of Procambarus clarkii, comprising the following steps: S1. Set feeding time , before feeding, extract the temperature data of the day from the weather forecast data of the meteorological monitoring department to form a temperature vector after feeding , according to the feeding activity of Procambarus clarkii and the temperature , calculate the corresponding feeding time point Weighted feeding coefficient and the feeding stability coefficient ; S2. According to the three growth stages of the Procambarus clarkii culture process, the corresponding basic requirement ratio of nutrient components is set respectively: the seedling stage, the growth stage and the adult stage. ; S3. According to the growth stage of the crayfish, select the corresponding basic requirement ratio of the nutritional components , and based on the weighted feeding coefficient after feeding and the feeding stability coefficient after feeding , calculate the ratio of each nutrient component , , , , in, represents the weighted feeding adjustment factor after feeding, represents the feeding stabilization adjustment factor after feeding, represents the sensitivity coefficient of nutrient i to the decrease in the mean value of feeding capacity, It represents the maximum value of the weighted feeding coefficient after feeding. represents the sensitivity coefficient of nutrient i to fluctuations in feeding capacity, represents the expected maximum value of the feeding stability coefficient; S4. Obtain the values ​​corresponding to each nutrient component Perform normalization processing to form a nutritional configuration prediction formula; S5. Collect all raw materials that can be used for the preparation of Procambarus clarkii feed, determine the content of the main nutrients in each raw material, and build a database of nutrient components of Procambarus clarkii formula raw materials; S6. According to the nutritional configuration prediction formula, extract all the data in the nutrient composition database of the raw materials of the crayfish formula, build and solve the linear programming model according to the minimum feed cost, and output the corresponding feeding time point The feed raw material formula of Procambarus clarkii is optimized to achieve nutritional configuration optimization.

[0005] Furthermore, step S1 includes the following steps: S21. Set feeding time Before feeding, extract the feeding time of the day from the weather forecast data of the meteorological monitoring department. After four consecutive time points , , , The temperature data after feeding is formed into a temperature vector , ; S22. Based on the relationship between feeding activity of Procambarus clarkii and temperature , determine the feeding coefficient of Procambarus clarkii , , in is the temperature in the crayfish farming area; S23, according to the feeding coefficient of Procambarus clarkii The calculation formula is to convert the temperature vector after feeding into Converted to feeding coefficient vector , ; S24, according to the feeding coefficient vector , introduce the weight vector , , , , , Represents the weight of feeding time after feeding, which decreases in sequence, and the weighted feeding coefficient after feeding is calculated , , is the feeding coefficient vector after feeding The transpose of S25, according to the feeding coefficient vector , calculate the feeding stability coefficient after feeding , , in, The internal elements are all the feeding coefficient vectors after feeding The mean of each element The vector formed, is the deviation vector The norm of .

[0006] Further, in step S3, and The determination includes the following steps: S31. Under laboratory control conditions, the temperature was adjusted four times continuously to observe the changes in the intake of various nutrients by Procambarus clarkii and record the utilization of nutrients by Procambarus clarkii. S32, calculate the weighted feeding coefficient after feeding and the feeding stability coefficient after feeding , and calculate the intake of each nutrient and the weighted feeding coefficient after feeding and the feeding stability coefficient after feeding The correlation coefficient of S33. Establishing the weighted feeding coefficient of nutrient intake and feeding and the feeding stability coefficient after feeding The regression model between them is used to obtain the regression coefficient; S34, normalizing the regression coefficient so that its value is within the interval [0,1], and determining the sensitivity coefficient of each nutrient component based on the normalized regression coefficient.

[0007] Further, in step S3, and The determination can be made by expert experience.

[0008] Furthermore, in step S3, the steps for determining the basic requirement ratio of the nutritional components are as follows: S51. Analyze the physiological characteristics of Procambarus clarkii at different growth stages and sort the requirements of protein, carbohydrates, fat, cellulose, vitamins and minerals in descending order; S52, analyzing the physiological characteristics of Procambarus clarkii at different growth stages, and setting a set of assignments that conform to an equidistant series for the requirements of the same nutrient component at different growth stages; S53, normalizing the determined nutritional components according to the three growth stages of the corresponding seedling stage, growth stage and adult stage; S54. Based on the preliminary determination Conduct small-scale breeding experiments, set up experimental and control groups, record growth rate, survival rate, feed conversion rate and other indicators, and evaluate the effects of nutritional components in the experimental group; S55. According to the evaluation results of the nutrient components of the experimental group, the proportion of each nutrient component is continuously adjusted to conduct multiple experiments, and finally a basic requirement ratio of nutrient components based on the experiment and the growth stage is obtained.

[0009] Further, in step S5, the construction of the nutritional component database of the raw materials of the Procambarus clarkii formula includes the following steps: S61. According to the dietary habits of Procambarus clarkii, collect all raw materials that can be used for preparing Procambarus clarkii feed; S62, consulting scientific literature and standard databases, extracting the corresponding nutritional component analysis data of the collected raw materials, and writing them into the nutritional component database of the raw materials of the Procambarus clarkii formula; S63. For the nutritional component analysis data of the collected raw materials that cannot be found in scientific literature and standard databases, laboratory analysis is used to determine the data, and the analysis data is written into the nutritional component database of the raw materials for the Procambarus clarkii formula; S64, collecting data on raw material prices on the Internet, converting them into price data in a unified unit, and writing the price data into a corresponding price field in a database of nutritional components of raw materials for Procambarus clarkii formula.

[0010] Furthermore, data on raw material prices collected on the Internet include feed raw material price information regularly released by industry associations and official websites, and futures exchange data on bulk feed raw materials.

[0011] Further, in step S6, a linear programming model is constructed and solved according to minimizing feed cost, including the following steps: S81. Construct objective function with the goal of minimizing feed cost , , in, is the unit cost of the jth raw material, is the decision variable, representing the proportion of the jth raw material in the feed, Z is the total cost, which is about the decision variable Function of S82. Establish constraint conditions, including nutrient composition constraint, total ratio constraint and non-negativity constraint, to form a raw material formula linear programming model; S83, substituting all the data in the raw material nutrient composition database of Procambarus clarkii into the raw material formula linear programming model, and solving for a corresponding feeding time point The feed raw material formula of Procambarus clarkii.

[0012] The present invention has the following beneficial effects due to the adoption of the above technology.

[0013] 1. The present invention sets the feeding time point and introduces the temperature forecast data of the day before feeding. The relationship between the weighted feeding coefficient and the feeding stability coefficient after feeding is calculated, which enables the nutritional formulation to dynamically respond to temperature changes and better meet the actual feeding capacity of crayfish.

[0014] 2. The present invention establishes an adjustment factor model based on the growth stage of crayfish and the calculated weighted feeding coefficient and feeding stability coefficient after feeding, optimizes the ratio of various nutrients, and fully considers the influence of average feeding capacity and feeding stability.

[0015] 3. The present invention constructs a raw material nutrient database specifically suitable for Procambarus clarkii through laboratory analysis, literature review and retrieval of data from corresponding databases, providing reliable data support for the preparation of feed formulas, so that the raw material selection and ratio can better meet the dynamic needs of Procambarus clarkii.

[0016] 4. When configuring feed according to the predicted nutritional composition ratio, the present invention uses linear programming to establish a mathematical model with the goal of minimizing feed cost. On the premise of meeting the nutritional needs of crayfish and feed quality, it can optimize the raw material combination and reduce feed production costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a step flowchart of the present invention.

[0018] Figure 2 It is a specific step block diagram of step S1 of the present invention.

[0019] Figure 3 The present invention determines in step S3 and Flow chart of the steps.

[0020] Figure 4It is a flowchart of the steps of determining the basic requirement ratio of the nutritional components in step S3 of the present invention.

[0021] Figure 5 It is a flowchart of the steps of constructing a nutritional component database of raw materials of Procambarus clarkii formula in step S5 of the present invention.

[0022] Figure 6 It is a flowchart of the steps of constructing and solving a linear programming model according to minimizing feed cost in step S6 of the present invention. DETAILED DESCRIPTION

[0023] Embodiment 1: Figure 1 As shown, the present invention provides a method for optimizing the nutritional formulation for the cultivation of Procambarus clarkii, comprising the following steps: S1. Set the daily feeding time , before feeding, extract the temperature data of the day from the weather forecast data of the meteorological monitoring department to form a temperature vector after feeding , according to the feeding activity of Procambarus clarkii and the temperature Calculate the corresponding feeding time Weighted feeding coefficient and the feeding stability coefficient after feeding ; S2. According to the three growth stages of the Procambarus clarkii culture process, the corresponding basic requirement ratio of nutrient components is set respectively: the seedling stage, the growth stage and the adult stage. , that is, the basic requirement ratio of nutrients corresponding to the three growth stages There are three, which need to be obtained through experimental determination in the early stage of operation; S3. According to the growth stage of the crayfish, select the corresponding basic requirement ratio of the nutritional components , and based on the weighted feeding coefficient after feeding and the feeding stability coefficient after feeding , calculate the ratio of each nutrient component , , , , in, represents the weighted feeding adjustment factor after feeding, represents the feeding stabilization adjustment factor after feeding, represents the sensitivity coefficient of nutrient i to the decrease in the mean value of feeding capacity, It represents the maximum value of the weighted feeding coefficient after feeding. represents the sensitivity coefficient of nutrient i to fluctuations in feeding capacity, represents the expected maximum value of the feeding stability coefficient; S4. Obtain the values ​​corresponding to each nutrient component Perform normalization processing to form a nutritional configuration prediction formula; S5. Collect all raw materials that can be used for the preparation of Procambarus clarkii feed, determine the content of the main nutrients in each raw material, and build a database of nutrient components of Procambarus clarkii formula raw materials; S6. According to the nutritional configuration prediction formula, extract all the data in the nutrient composition database of the raw materials of the crayfish formula, build and solve the linear programming model according to the minimum feed cost, and output the corresponding feeding time point The feed raw material formula of Procambarus clarkii is optimized to achieve nutritional configuration optimization.

[0024] like Figure 2 As shown, step S1 includes the following steps: S21. Set feeding time Before feeding, extract the feeding time of the day from the weather forecast data of the meteorological monitoring department. After four consecutive time points , , , The temperature data after feeding is formed into a temperature vector , ; S22. Based on the relationship between feeding activity of Procambarus clarkii and temperature That is, when the temperature is between 22°C-30°C, crayfish grow most vigorously. Therefore, when constructing the function, the feeding coefficient is set to 1, at which time their feeding and growth rates are optimal; if the temperature is lower than 18°C, the growth of crayfish is inhibited, and the feeding coefficient is set to 0, because at lower temperatures, the metabolism and activity of crayfish are significantly reduced, and they almost stop feeding; when the temperature is higher than 32°C, feeding is also inhibited, and the feeding coefficient is 0. High temperature will cause stress response in crayfish, affecting their growth and feeding ability; when the temperature is between 18°C-22°C or 30°C-32°C, these two intervals belong to the unsuitable temperature range. Although they will not completely stop feeding, the feeding coefficient will be lower than 1, indicating that the crayfish's feeding amount and growth rate are inhibited to a certain extent, thereby determining the feeding coefficient of Procambarus clarkii , , in is the temperature in the Procambarus clarkii culture area; S23, according to the feeding coefficient of Procambarus clarkii The calculation formula is to convert the temperature vector after feeding into Converted to feeding coefficient vector , ; S24, according to the feeding coefficient vector , introduce the weight vector , , , , , Represents the weight of feeding time after feeding, which decreases in sequence, and the weighted feeding coefficient after feeding is calculated , , is the feeding coefficient vector after feeding The transpose of S25, according to the feeding coefficient vector , calculate the feeding stability coefficient after feeding , , in, The internal elements are all the feeding coefficient vectors after feeding The mean of each element The vector formed, is the deviation vector The norm of .

[0025] like Figure 3 As shown, in step S3, and The determination includes the following steps: S31. Under laboratory control conditions, the temperature was adjusted four times continuously to observe the changes in the intake of various nutrients by Procambarus clarkii and record the utilization of nutrients by Procambarus clarkii. S32, calculate the weighted feeding coefficient after feeding and the feeding stability coefficient after feeding , and calculate the intake of each nutrient and the weighted feeding coefficient after feeding and the feeding stability coefficient after feeding The correlation coefficient of S33. Establishing the weighted feeding coefficient of nutrient intake and feeding and the feeding stability coefficient after feeding The regression model between them is used to obtain the regression coefficient; S34, normalizing the regression coefficient so that its value is within the interval [0,1], and determining the sensitivity coefficient of each nutrient component based on the normalized regression coefficient.

[0026] In step S3, and The determination of settings is made by expert experience.

[0027] like Figure 4 As shown, in step S3, the steps for determining the basic requirement ratio of the nutritional components are as follows: S51. According to the physiological characteristics of different growth stages of Procambarus clarkii, the requirements for protein, carbohydrates, fats, cellulose, vitamins and minerals are sorted in descending order. For example, the first seedling stage (1-3 months, G=1) is characterized by rapid growth, high demand for high-quality protein, and the digestive system is not fully developed. At this time, the nutritional requirements are protein: high demand, for tissue growth, fat: moderate, provide energy, carbohydrates: moderate, provide energy, cellulose: low demand, limited digestion capacity, vitamins and minerals: high demand, promote development and immunity. Second, the growth period (3-6 months, G=2), characteristics: continuous growth, enhanced metabolic activity, and improved digestion capacity. At this time, the nutritional requirements are protein: high demand, support continuous growth, fat and sugar: increased demand, provide energy, cellulose: moderate, promote digestive function, vitamins and minerals: maintain appropriate levels. Adult stage (more than 6 months, G=3), characteristics: slowed growth rate, sexual maturity, and reproductive needs. At this time, the nutritional requirements are protein: the demand is reduced, but still needs to be maintained; fat and carbohydrates: the demand increases to meet energy and reproduction needs; cellulose: moderate to maintain digestive health; vitamins and minerals: support reproductive function. ; S52. According to the physiological characteristics of Procambarus clarkii at different growth stages, a set of values ​​that conform to the equally spaced series are set for the requirements of the same nutrient component at different growth stages. For example, for protein, seedling stage: high proportion (such as 40%), growth stage: slightly lower than seedling stage (such as 35%), adult stage: further reduced (such as 30%); fat, seedling stage: medium proportion (such as 10%), growth stage: increase (such as 15%), adult stage: further increased (such as 20%); carbohydrates, seedling stage: medium proportion (such as 15%), growth stage: increase (such as 25%), adult stage: maintain or slightly increase (such as 25%); cellulose, Seedling stage: low ratio (such as 5%), growth stage: increase (such as 10%), adult stage: maintain (such as 10%), vitamins and minerals, maintain appropriate ratios (such as 5%-10%) at each stage; S53, normalizing the determined nutritional components according to the three growth stages of the corresponding seedling stage, growth stage and adult stage; S54. Based on the preliminary determination Conduct small-scale breeding experiments, set up experimental and control groups, record growth rate, survival rate, feed conversion rate and other indicators, and evaluate the effects of nutritional components in the experimental group; S55. According to the evaluation results of the nutrient components of the experimental group, the proportion of each nutrient component is continuously adjusted to conduct multiple experiments, and finally a basic requirement ratio of nutrient components based on the experiment and the growth stage is obtained.

[0028] like Figure 5 As shown, in step S5, the construction of the nutritional component database of the raw material formula of Procambarus clarkii includes the following steps: S61. According to the dietary habits of Procambarus clarkii, collect all raw materials that can be used for preparing Procambarus clarkii feed; S62, consulting scientific literature and standard databases, such as the Chinese feed database in China, the Feedipedia and NRC Nutrient Requirements databases abroad, extracting the corresponding nutritional component analysis data of the collected raw materials, and writing them into the nutritional component database of the raw materials for the Procambarus clarkii formula; S63. For the nutritional component analysis data of the collected raw materials that cannot be found in scientific literature and standard databases, laboratory analysis is used to determine the data, and the analysis data is written into the nutritional component database of the raw materials for the Procambarus clarkii formula; S64, collecting data on raw material prices on the Internet, converting them into price data in a unified unit, and writing the price data into a corresponding price field in a database of nutritional components of raw materials for Procambarus clarkii formula.

[0029] Among them, the data on raw material prices collected on the Internet include feed raw material price information regularly released by industry associations and official websites, and futures exchange data on bulk feed raw materials.

[0030] Among them, the laboratory analysis method to determine the nutritional composition of the collected raw materials mainly includes the following steps: S71. Collect raw material samples to ensure that the collected raw material samples are representative, covering the changes of different batches, origins and seasons. At the same time, the samples are homogenized to prevent the deviation of analysis results caused by uneven components; S72. According to the requirements of feed formula, determine the nutrients that need to be analyzed, including conventional nutrients and specific nutrients. Conventional nutrients include crude protein (CP), crude fat (EE), crude fiber (CF), nitrogen-free extract (NFE), crude ash (Ash) and moisture (Moisture), while specific nutrients include amino acid spectrum, fatty acid composition, vitamin content, mineral elements (macro and trace elements), anti-nutritional factors (such as phytic acid, tannin, etc.); S73. Select analytical methods, among which commonly used analytical methods include Kjeldahl or Dumas for crude protein, Soxhlet extraction for crude fat, acid-base digestion for crude fiber, high performance liquid chromatography (HPLC) for amino acids, gas chromatography (GC) for fatty acids, enzyme-linked immunosorbent assay (ELISA) or high performance liquid chromatography for vitamins, and atomic absorption spectrometry (AAS) or inductively coupled plasma emission spectrometry (ICP) for minerals; S74. After calibrating the analytical instrument, start laboratory analysis, conduct multiple measurements on the same sample, take the average value, and convert all nutrient contents to dry matter (DM) basis for easy comparison and calculation.

[0031] like Figure 6 As shown, in step S6, a linear programming model is constructed and solved according to minimizing feed cost, including the following steps: S81. Construct objective function with the goal of minimizing feed cost , , in, is the unit cost of the jth raw material, is the decision variable, representing the proportion of the jth raw material in the feed, such as fish meal, soybean meal, corn, wheat bran and fish oil, etc. Z is the total cost, which is about the decision variable Function of S82. Establish constraints, including nutrient composition constraints, total ratio constraints, and non-negativity constraints, to form a raw material formula linear programming model, where the nutrient composition constraints are , is the content of the ith nutrient in the jth raw material, is the minimum requirement of the ith nutrient in the feed, where the total proportion constraint is , is a decision variable, representing the proportion of the jth raw material in the feed, where the non-negativity constraint is , ; S83, substituting all the data in the raw material nutrient composition database of Procambarus clarkii into the raw material formula linear programming model, and solving for a corresponding feeding time point The raw material formula of Procambarus clarkii feed; S84, according to this corresponding feeding time point The feed is prepared according to the feed processing technology (such as granulation and puffing) and then fed at the feeding time. Feed the feed.

Claims

1. A method for optimizing the nutritional formulation of Procambarus clarkii culture, characterized in that: The steps include: S1. Set feeding time , before feeding, extract the temperature data of the day from the weather forecast data of the meteorological monitoring department to form a temperature vector after feeding , according to the feeding activity of Procambarus clarkii and the temperature , calculate the corresponding feeding time point Weighted feeding coefficient and the feeding stability coefficient ; S2. According to the three growth stages of the Procambarus clarkii culture process, the corresponding basic requirement ratio of nutrient components is set respectively: the seedling stage, the growth stage and the adult stage. ; S3. According to the growth stage of the crayfish, select the corresponding basic requirement ratio of the nutritional components , and based on the weighted feeding coefficient after feeding and the feeding stability coefficient , calculate the ratio of each nutrient component , ， ， ， in, represents the weighted feeding adjustment factor after feeding, represents the feeding stabilization adjustment factor after feeding, represents the sensitivity coefficient of nutrient i to the decrease in the mean value of feeding capacity, It represents the maximum value of the weighted feeding coefficient after feeding. represents the sensitivity coefficient of nutrient i to fluctuations in feeding capacity, represents the expected maximum value of the feeding stability coefficient; S4. Obtain the values ​​corresponding to each nutrient component Perform normalization processing to form a nutritional configuration prediction formula; S5. Collect all raw materials that can be used for the preparation of Procambarus clarkii feed, determine the content of the main nutrients in each raw material, and build a database of nutrient components of Procambarus clarkii formula raw materials; S6. According to the nutritional configuration prediction formula, extract all the data in the nutrient composition database of the raw materials of the crayfish formula, build and solve the linear programming model according to the minimum feed cost, and output the corresponding feeding time point The feed raw material formula of Procambarus clarkii is optimized to achieve nutritional configuration optimization.

2. The method for optimizing the nutritional formulation for the cultivation of Procambarus clarkii according to claim 1, characterized in that: Step S1 includes the following steps: S21. Set feeding time Before feeding, extract the feeding time of the day from the weather forecast data of the meteorological monitoring department. After four consecutive time points , , , The temperature data after feeding is formed into a temperature vector , ; S22. Based on the relationship between feeding activity of Procambarus clarkii and temperature , determine the feeding coefficient of Procambarus clarkii , ， in is the temperature in the Procambarus clarkii culture area; S23, according to the feeding coefficient of Procambarus clarkii The calculation formula is to convert the temperature vector after feeding into Converted to feeding coefficient vector , ; S24, according to the feeding coefficient vector , introduce the weight vector , , , , , Represents the weight of feeding time after feeding, which decreases in sequence, and the weighted feeding coefficient after feeding is calculated , , is the feeding coefficient vector after feeding The transpose of S25, according to the feeding coefficient vector , calculate the feeding stability coefficient after feeding , ， in, The internal elements are all the feeding coefficient vectors after feeding The mean of each element The vector formed, is the deviation vector The norm of .

3. The method for optimizing the nutritional formulation for the cultivation of Procambarus clarkii according to claim 1, characterized in that: In step S3, and The determination includes the following steps: S31. Under laboratory control conditions, the temperature was adjusted four times continuously to observe the changes in the intake of various nutrients by Procambarus clarkii and record the utilization of nutrients by Procambarus clarkii. S32, calculate the weighted feeding coefficient after feeding and the feeding stability coefficient after feeding , and calculate the intake of each nutrient and the weighted feeding coefficient after feeding and the feeding stability coefficient after feeding The correlation coefficient of S33. Establishing the weighted feeding coefficient of nutrient intake and feeding and the feeding stability coefficient after feeding The regression model between them is used to obtain the regression coefficient; S34, normalizing the regression coefficient so that its value is within the interval [0,1], and determining the sensitivity coefficient of each nutrient component based on the normalized regression coefficient.

4. The method for optimizing the nutritional formulation for the cultivation of Procambarus clarkii according to claim 1, characterized in that: In step S3, and The determination of settings is made by expert experience.

5. The method for optimizing the nutritional formulation for the cultivation of Procambarus clarkii according to claim 1, characterized in that: In step S3, the steps for determining the basic requirement ratio of the nutritional components are as follows: S51. Analyze the physiological characteristics of Procambarus clarkii at different growth stages and sort the requirements of protein, carbohydrates, fat, cellulose, vitamins and minerals in descending order; S52, analyzing the physiological characteristics of Procambarus clarkii at different growth stages, and setting a set of assignments that conform to an equidistant series for the requirements of the same nutrient component at different growth stages; S53, normalizing the determined nutritional components according to the three growth stages of the corresponding seedling stage, growth stage and adult stage; S54. Based on the preliminary determination Conduct small-scale breeding experiments, set up experimental and control groups, record growth rate, survival rate, feed conversion rate and other indicators, and evaluate the effects of nutritional components in the experimental group; S55. According to the evaluation results of the nutrient components of the experimental group, the proportion of each nutrient component is continuously adjusted to conduct multiple experiments, and finally a basic requirement ratio of nutrient components based on the experiment and the growth stage is obtained.

6. The method for optimizing the nutritional formulation for the cultivation of Procambarus clarkii according to claim 1, characterized in that: In step S5, the construction of the nutritional component database of the raw materials of the Procambarus clarkii formula includes the following steps: S61. According to the dietary habits of Procambarus clarkii, collect all raw materials that can be used for preparing Procambarus clarkii feed; S62, consulting scientific literature and standard databases, extracting the corresponding nutritional component analysis data of the collected raw materials, and writing them into the nutritional component database of the raw materials of the Procambarus clarkii formula; S63. For the nutritional component analysis data of the collected raw materials that cannot be found in scientific literature and standard databases, laboratory analysis is used to determine the data, and the analysis data is written into the nutritional component database of the raw materials for the Procambarus clarkii formula; S64, collecting data on raw material prices on the Internet, converting them into price data in a unified unit, and writing the price data into a corresponding price field in a database of nutritional components of raw materials for Procambarus clarkii formula.

7. The method for optimizing the nutritional formulation for the cultivation of Procambarus clarkii according to claim 6, characterized in that: The data on raw material prices collected on the Internet include feed raw material price information regularly released by industry associations and official websites, and futures exchange data on bulk feed raw materials.

8. The method for optimizing the nutritional formulation for the cultivation of Procambarus clarkii according to claim 1, characterized in that: In step S6, a linear programming model is constructed and solved according to minimizing feed cost, including the following steps: S81. Construct objective function with the goal of minimizing feed cost , , in, is the unit cost of the jth raw material, is the decision variable, representing the proportion of the jth raw material in the feed, Z is the total cost, which is about the decision variable Function of S82. Establish constraint conditions, including nutrient composition constraint, total ratio constraint and non-negativity constraint, to form a raw material formula linear programming model; S83, substituting all the data in the raw material nutrient composition database of Procambarus clarkii into the raw material formula linear programming model, and solving for a corresponding feeding time point The feed raw material formula of Procambarus clarkii.

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